ArticleiScience2023
Multi-scale spatial modeling of immune cell distributions enables survival prediction in primary central nervous system lymphoma.
Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed.
- Distinct Spatial Immune Architectures in Tumor and Tumor-Adjacent Tissues of Early-Stage Non-Small Cell Lung Cancer.bioRxiv : the preprint server for biology · 2026Article
- Article
- Spatial analysis of malignant-immune cell interactions in the tumor microenvironment using topological data analysis.NPJ systems biology and applications · 2026Article
- Unraveling the immune microenvironment in primary CNS lymphoma.Biomarker research · 2026Review
- Recovering missing features in nonnegative matrix factorization via generalized singular value decomposition.iScience · 2026Article
- Review
- Article
- Immune and non-immune cell fencing of tumor cells is a widespread and functionally relevant spatial pattern in solid cancers.Computational and structural biotechnology journal · 2025Article
- SpatialSort: a Bayesian model for clustering and cell population annotation of spatial proteomics data.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To understand the clinical significance of the tumor microenvironment (TME), it is essential to study the interactions between malignant and non-malignant cells in clinical specimens. Here, we established a computational framework for a multiplex imaging system to comprehensively characterize spatial contexts of the TME at multiple scales, including close and long-distance spatial interactions between cell type pairs. We applied this framework to a total of 1,393 multiplex imaging data newly generated from 88 primary central nervous system lymphomas with complete follow-up data and identified significant prognostic subgroups mainly shaped by the spatial context. A supervised analysis confirmed a significant contribution of spatial context in predicting patient survival. In particular, we found an opposite prognostic value of macrophage infiltration depending on its proximity to specific cell types. Altogether, we provide a comprehensive framework to analyze spatial cellular interaction that can be broadly applied to other technologies and tumor contexts.
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Registered trials
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